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An extensible benchmark for evaluating large language models on planning

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I was trying to go through the code and wanted to add a new domain to evaluate my LLM on that domain. So my question was how have you generated...

`python3 llm_plan_pipeline.py --task TASK --config CONFIG --engine ENGINE [--ignore_existing] [--run_till_completion RUN-TILL-COMPLETION] [--specific_instances SPECIFIC-INSTANCES] [--random_example RANDOM-EXAMPLE] [--verbose VERBOSE] [--seed SEED]` Also, is there a default config.yaml example you might share? Thanks.

Hi, I fixed some error in the code (e.g. yaml instead of json, domain_name instead of domain and other things that just dont work othewise)